MTech (Data Analytics) at JIIT: A draft curriculum for comments and suggestions

Posted on April 13, 2015

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Author:   Sanjay Goel

This program is being rolled out from 2015-16.   The detailed curriculum is under development and consideration for approvals.  Meanwhile,  I invite the professionals working in this area to give their considered comments and suggestions on this draft.

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Data Analytics involves using computing for reporting, analysis, monitoring, and prediction. Data Analytics has been well recognized as one of the fastest growing areas in knowledge economies.  All business and government organisation working in commerce, policy, insurance, finance, economics, engineering, infrastructure, energy, health care, education, security, sports, media, culture, etc. are increasing relying on computational tools and techniques of data analytics for taking informed decisions.  International Data Corporation (IDC) forecasts that business analytics market will reach $50.7 billion in 2016. According to Avendus Capital, US alone is expected to have a shortage of 140,000 – 190,000 analytics professionals by 2018..  NASSCOM predicts that the analytics market in India could reach $2.3 billion by the end of 2017-18.

In India, a good number of consulting, KPO and IT companies are providing specialised services in the field of  data analytics.  Some are providing general solutions in all segments whereas some others are specialising in specific verticals like banking, retail, marketing, financial, CRM, risk analysis, web, clinical, telecom, insurance, etc. These companies include- IBM Analytics, Mu-Sigma, LatentView, HCL Technologies, Accenture, Genpact Analytics, Cognizant Analytics, TCS Analytics, Wipro Analytics, McKinsey Analytics Knowledge Centre, Deloitte Analytics, PwC Analytics, AbsolutData, Fractal Analytics, iCreate, Dunhumby, Global Analytics, Manhattan Systems, Capillary Technologies, Nabler, Activecubes, ICRA Technology Services, WNS Analytics, Opera Solutions, Data Monitor,  Ipsos, EXL Services, Meritus, Modelytics, Bridge i2i Analytics, Cytel, Neural Techsoft (Financial & Risk Analytics), Vehere Interactive, Aegis Global, Datamatics, Marketelligent, TNS Global, NettPositive Analytics, Affine Analytics, EVALUESERVE, Innovacer, Crisp Analytics.

In addition, many other captive companies/groups provide solutions to their parent organisation like.  These include – HSBC Analytics, Citi Bank Analytics, American Express, Fidelity Analytics,   GE Capital,   RBS Business Services, Barclays Shared Services, Target Analytics, Spencer Analytics, Amazon Analytics, Dell Analytics, HP Analytics, eBay / PayPal, Experian India, Fair Isaac India, Dun & Bradstreet.

Further, a large number of new IT ventures are starting in this area to fill the global demand and talent gap in this area.  Telangana state government has already announced a knowledge park on Data Analytics.

Program Objectives:

MTech (Data Analytics) is an interdisciplinary program offered by department of CSE & IT at JIIT and is designed to meet the huge manpower shortage in this area. This program has been designed to develop the ability to apply and develop computational techniques and systems to draw insights from big data in a variety of application domains. It is expected that the  graduates of the proposed program will mostly join the fast growing Data Analytics industry as technical experts and some will even launch their own IT start-ups in this field. Some graduates will choose to go for doctoral studies and/or pursue their career in academia. The available and growing academic opportunities being developed through our ongoing MTech programs in ‘CSE’ and ‘IT and Entrepreneurship’ will also be leveraged to enrich this program with advanced level computer science courses in various areas on one hand and design and entrepreneurship related courses on the other.  Jaiprakash Centre for Entrepreneurship Development (JCED) will also support the students’ entrepreneurial activity that spins off from this program.

The curriculum exposes students with all aspects of data analytics including research design, data collection, preparation, analysis, integration, visualization, and interpretation. In addition to the CSE & IT department, the department of mathematics as well as business school/department of HSS will also contribute courses for this program.   The core courses include statistical data analysis, financial econometrics, data warehousing and data mining, pattern recognition and machine learning, large scale graph analytics, empirical research and laboratories.  Students will also be offered several electives on theoretical, systemic, algorithmic, and applied aspects of data analytics.   In addition to the CSE & IT department, the department of mathematics as well as business school/department of HSS will also contribute courses for this program.

Eligibility: 

1.   BTech (in any discipline) or equivalent

2.   Masters (in Computer Applications/Computer Science/IT/Maths/Statistics/Operations Research/Physics/ Electronics/    Instrumentation/Economics/Commerce) or equivalent

Credits:  70

Duration:   2 years, 4 semester;

1st year:   course work;

2nd year:   Full time Internship (14 credits in 3rd sem) and Disseration/industry project (18 credits in 4th sem)

Bridge Course:  One of the following courses:  3 credits  (1st sem)

1.  Econometrics  – Not allowed for students with MA (Economics)

2.   Software Development – Not allowed for students with CS/IT/MCA background

Core Courses:

  1. Mathematics for Data Analytics        – 3 credits    (1st sem)
  2. Data warehousing and Data mining – 3 credits    (1st sem)
  3. Machine Learning                             – 3 credits    (1st sem)
  4. IT Venture Creation                          – 3 credits    (1st sem)
  5. Data Analytics Lab                           – 2 credits    (2nd sem)   (Tools like R etc.)
  6. Big Data Technologies                     – 3 credits    (2nd sem)
  7. Large Scale Graph Analytics            – 3 credits    (2nd sem)
  8. Empirical Research                          – 2 credits    (2nd sem)
  9. Advanced Data Analytics Lab OR  Part time Industrial internship          –  2 credits   (2nd sem)

Electives:    (4 electives:  Three of 3 credits each and one of 2 credits;     One in 1st sem and three  in 2nd sem)

      1. Game Theory and Business Intelligence (by JBS/HSS)
      2. CRM Analytics (by JBS)
      3. Data Analytics for Bioinformatics (by Biotech)
      4. Cloud Computing
      5. Advanced Machine Learning
      6. Interactive Data Analysis
      7. Spatial and Temporal Data Analytics
      8. Ecommerce and Social Media Analytics
      9. Large Scale databases
      10. Big Data Analytics
      11. Mobile and IoT Analytics
      12. Multimedia Analytics
      13. Forensic Analytics
      14. Information Integration and Visualization
      15. Web Algorithms
      16. Information Retrieval
      17. Natural Language Processing
      18. Computer Vision
      19. Qualitative Research and Data Analysis
      20. Predictive Analytics
      21. Distributed Systems
      22. High Performance Software Engineering
      23. Advanced Algorithms
    • Any core/ elective course offered MTech (CSE)/MTech (IT&E)/MTech (ACM) can be opened for this program as well.

Syllabus Overview of Bridge and Core courses:

1.   Econometrics: (3 credits):  Regression, Multivariate regression, Heteroscedasticity and autocorrelation, Simultaneous equation models, Microeconometrics, Macroeconometrics, Computational Tools

2.  Software Development: (3 credits): Python Programming, Database Programming, Introduction to cloud environment

3.   Mathematics for Data Analytics: (3 credits): Statistics, Multivariate Statistics, Linear programming, Markov Chains, Simulation, Computational Tools

4.    Data Warehousing and Data Mining: (3 credits):   Schema integration, Data cleaning, Deduplication, OLAP, Online aggregation;  Classification, Clustering, Pattern mining, ETL and other Computational Tools

5.    Machine Learning: (3 credits): Beysian reasoning, Decision trees, Dimensionality reduction, Unsupervised learning,  Optimisation and search, ANN, Support vector machine, Evolutional learning, Computational Tools

6.    IT Venture Creation: (3 credits):  IT industry and ventures, IT Entrepreneurship heuristics, IT venture business plan, strategies, and business models,   Design and analysis of business models for IT ventures, IT venture risk management, Lean start-up, IT venture planning tools

7.     Empirical Research: (2 credits): Philosophy of Knowledge, Research thinking, Qualitative research, Quantitative research,  Experiment design,  Data collection, Data analysis, Data visualisation,  Theory building, Empirical research in engineering, information systems, business, policy making, and social sciences, Computational Tools

8.     Big Data Technologies: (3 credits): Big data, Structured data, Unstructured data, Big data programming (Hadoop/HDFS, Map-reduce, Apache Spark, event processing), NSQL databases, data computing appliance (DCA) and OLAP, Massive parallel processing, Big Data Analytics

9.     Large Scale Graph Analytics: (3 credits):  Large scale graph representation and storage, Social networks, Indexing techniques for large graphs, graph compression, query processing, evolving graphs, heterogeneous graphs, integrating graph with non graph data, distributed graph management, large scale graph visualisation, Computational Tools

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